Book ChapterDOI
Multicriteria Decision Analysis for Intrusion Detection Data
Sanjiban Sekhar Roy,Omsai Jadhav,Saptarshi Chakraborty,Swapnil Saurav,Madhu Viswanatham +4 more
- pp 667-672
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TLDR
How dominance based rough set approach can be useful for analysis and evaluation of intrusion detection data set is shown.Abstract:
Uncertain data can be dealt with rough set theory and dominance based rough set approach which is an extension to the classical rough set theory is a new mathematical technique to deal with multicriteria indecisive data. Here in this paper we have shown how dominance based rough set approach can be useful for analysis and evaluation of intrusion detection data set.read more
Citations
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Proceedings ArticleDOI
Analyzing Intrusion Detection System: An ensemble based stacking approach
TL;DR: An IDS model, which classifies different types of intrusion attacks based on Stacking classifier, which has achieved good accuracy while classifying the KDD-Cup 99 dataset and that has been achieved with 10 fold cross validation.
References
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Journal ArticleDOI
Rough sets
TL;DR: This approach seems to be of fundamental importance to artificial intelligence (AI) and cognitive sciences, especially in the areas of machine learning, knowledge acquisition, decision analysis, knowledge discovery from databases, expert systems, decision support systems, inductive reasoning, and pattern recognition.
Journal ArticleDOI
Rough sets theory for multicriteria decision analysis
TL;DR: The original rough set approach proved to be very useful in dealing with inconsistency problems following from information granulation, but is failing when preference-orders of attribute domains (criteria) are to be taken into account and it cannot handle inconsistencies following from violation of the dominance principle.
Proceedings ArticleDOI
A data mining framework for building intrusion detection models
TL;DR: A data mining framework for adaptively building Intrusion Detection (ID) models is described, to utilize auditing programs to extract an extensive set of features that describe each network connection or host session, and apply data mining programs to learn rules that accurately capture the behavior of intrusions and normal activities.
Journal ArticleDOI
Rough approximation of a preference relation by dominance relations
TL;DR: An original methodology for using rough sets to preference modeling in multi-criteria decision problems is presented, including pairs of actions described by graded preference relations on particular criteria and by a comprehensive preference relation.
Journal ArticleDOI
A unified approach to reducts in dominance-based rough set approach
TL;DR: This paper proposes a new approach to reducts in DRSA and proves that they are consolidated into four kinds, and shows that all kinds of reduCTs can be enumerated based on two discernibility matrices.